Fix gamma values: video 2.2, texture 2.1, add GLB Raw export
Browse files- Video: Set to standard gamma 2.2 for proper brightness
- Texture: Set to gamma 2.1 (slightly darker to reduce over-brightness)
- Add GLB Raw export with minimal processing (50% simplification, no hole filling)
- Fixes: video now properly bright, textures slightly less bright than before
- app.py +43 -4
- trellis/utils/postprocessing_utils.py +71 -1
- trellis/utils/render_utils.py +1 -1
app.py
CHANGED
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@@ -227,6 +227,35 @@ def extract_glb(
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return glb_path, glb_path
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@spaces.GPU
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def extract_gaussian(state: dict, req: gr.Request) -> Tuple[str, str]:
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"""
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@@ -319,6 +348,7 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
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with gr.Row():
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extract_glb_btn = gr.Button("Extract GLB", interactive=False)
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extract_gs_btn = gr.Button("Extract Gaussian", interactive=False)
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gr.Markdown("""
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*NOTE: Gaussian file can be very large (~50MB), it will take a while to display and download.*
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@@ -391,13 +421,13 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
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inputs=[image_prompt, multiimage_prompt, is_multiimage, seed, ss_guidance_strength, ss_sampling_steps, slat_guidance_strength, slat_sampling_steps, multiimage_algo],
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outputs=[output_buf, video_output],
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).then(
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lambda: tuple([gr.update(interactive=True), gr.update(interactive=True)]),
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outputs=[extract_glb_btn, extract_gs_btn],
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)
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video_output.clear(
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lambda: tuple([gr.update(interactive=False), gr.update(interactive=False)]),
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outputs=[extract_glb_btn, extract_gs_btn],
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)
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extract_glb_btn.click(
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@@ -409,6 +439,15 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
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outputs=[download_glb],
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)
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extract_gs_btn.click(
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extract_gaussian,
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inputs=[output_buf],
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return glb_path, glb_path
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+
@spaces.GPU(duration=90)
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+
def extract_glb_raw(
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state: dict,
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texture_size: int,
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req: gr.Request,
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) -> Tuple[str, str]:
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"""
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+
Extract a RAW GLB file from the 3D model with minimal processing.
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Skips hole filling and uses only light simplification (50% instead of 90%).
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Preserves more original geometry from the neural network.
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Args:
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state (dict): The state of the generated 3D model.
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texture_size (int): The texture resolution.
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Returns:
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str: The path to the extracted raw GLB file.
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"""
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if state is None:
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raise gr.Error("Please generate a 3D model first before extracting GLB.")
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user_dir = os.path.join(TMP_DIR, str(req.session_hash))
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gs, mesh = unpack_state(state)
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glb = postprocessing_utils.to_glb_raw(gs, mesh, texture_size=texture_size, verbose=True)
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glb_path = os.path.join(user_dir, 'sample_raw.glb')
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glb.export(glb_path)
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torch.cuda.empty_cache()
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return glb_path, glb_path
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+
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@spaces.GPU
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def extract_gaussian(state: dict, req: gr.Request) -> Tuple[str, str]:
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"""
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with gr.Row():
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extract_glb_btn = gr.Button("Extract GLB", interactive=False)
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+
extract_glb_raw_btn = gr.Button("Extract GLB Raw (Minimal Processing)", interactive=False, variant="secondary")
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extract_gs_btn = gr.Button("Extract Gaussian", interactive=False)
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gr.Markdown("""
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*NOTE: Gaussian file can be very large (~50MB), it will take a while to display and download.*
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inputs=[image_prompt, multiimage_prompt, is_multiimage, seed, ss_guidance_strength, ss_sampling_steps, slat_guidance_strength, slat_sampling_steps, multiimage_algo],
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outputs=[output_buf, video_output],
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).then(
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lambda: tuple([gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True)]),
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outputs=[extract_glb_btn, extract_glb_raw_btn, extract_gs_btn],
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)
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video_output.clear(
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lambda: tuple([gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False)]),
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outputs=[extract_glb_btn, extract_glb_raw_btn, extract_gs_btn],
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)
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extract_glb_btn.click(
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outputs=[download_glb],
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)
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extract_glb_raw_btn.click(
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extract_glb_raw,
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inputs=[output_buf, texture_size],
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outputs=[model_output, download_glb],
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).then(
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lambda: gr.update(interactive=True),
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outputs=[download_glb],
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)
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extract_gs_btn.click(
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extract_gaussian,
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inputs=[output_buf],
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trellis/utils/postprocessing_utils.py
CHANGED
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@@ -340,7 +340,7 @@ def bake_texture(
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# 🔧 Apply gamma correction (Linear → sRGB)
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# Fixes "dark model" issue by converting from linear color space to sRGB
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texture_linear = texture.reshape(texture_size, texture_size, 3).cpu().numpy()
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-
texture_srgb = np.power(np.clip(texture_linear, 0, 1), 1.0/2.
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texture = np.clip(texture_srgb * 255, 0, 255).astype(np.uint8)
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# inpaint
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@@ -406,6 +406,76 @@ def bake_texture(
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return texture
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def to_glb(
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app_rep: Union[Strivec, Gaussian],
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mesh: MeshExtractResult,
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# 🔧 Apply gamma correction (Linear → sRGB)
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# Fixes "dark model" issue by converting from linear color space to sRGB
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texture_linear = texture.reshape(texture_size, texture_size, 3).cpu().numpy()
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+
texture_srgb = np.power(np.clip(texture_linear, 0, 1), 1.0/2.1) # Gamma 2.1 (slightly darker than standard 2.2)
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texture = np.clip(texture_srgb * 255, 0, 255).astype(np.uint8)
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# inpaint
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return texture
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+
def to_glb_raw(
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app_rep: Union[Strivec, Gaussian],
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mesh: MeshExtractResult,
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texture_size: int = 1024,
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verbose: bool = True,
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) -> trimesh.Trimesh:
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"""
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Convert a generated asset to a GLB file with MINIMAL processing.
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Skips hole filling and uses light simplification only.
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This preserves more original geometry while keeping GPU usage manageable.
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+
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Args:
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app_rep (Union[Strivec, Gaussian]): Appearance representation.
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mesh (MeshExtractResult): Extracted mesh.
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texture_size (int): Size of the texture.
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verbose (bool): Whether to print progress.
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"""
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vertices = mesh.vertices.cpu().numpy()
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faces = mesh.faces.cpu().numpy()
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if verbose:
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print(f'🔧 RAW GLB: Starting with {vertices.shape[0]} vertices, {faces.shape[0]} faces')
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# LIGHT simplification only (50% reduction instead of 90%)
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# This keeps GPU usage manageable while preserving more detail
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import pyvista as pv
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mesh_pv = pv.PolyData(vertices, np.concatenate([np.full((faces.shape[0], 1), 3), faces], axis=1))
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mesh_pv = mesh_pv.decimate(0.5, progress_bar=verbose)
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vertices, faces = mesh_pv.points, mesh_pv.faces.reshape(-1, 4)[:, 1:]
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if verbose:
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print(f'🔧 RAW GLB: After light simplification: {vertices.shape[0]} vertices, {faces.shape[0]} faces')
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# parametrize mesh (required for texture)
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vertices, faces, uvs = parametrize_mesh(vertices, faces)
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if verbose:
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print(f'🔧 RAW GLB: After UV unwrap: {vertices.shape[0]} vertices, {faces.shape[0]} faces')
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# bake texture (same as normal)
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observations, extrinsics, intrinsics = render_multiview(app_rep, resolution=1024, nviews=100)
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masks = [np.any(observation > 0, axis=-1) for observation in observations]
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extrinsics = [extrinsics[i].cpu().numpy() for i in range(len(extrinsics))]
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intrinsics = [intrinsics[i].cpu().numpy() for i in range(len(intrinsics))]
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texture = bake_texture(
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vertices, faces, uvs,
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observations, masks, extrinsics, intrinsics,
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texture_size=texture_size, mode='opt',
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lambda_tv=0.01,
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verbose=verbose
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)
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texture = Image.fromarray(texture)
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# rotate mesh (from z-up to y-up)
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vertices = vertices @ np.array([[1, 0, 0], [0, 0, -1], [0, 1, 0]])
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# Create material
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material = trimesh.visual.material.PBRMaterial(
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baseColorTexture=texture
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)
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mesh = trimesh.Trimesh(vertices, faces, visual=trimesh.visual.TextureVisuals(uv=uvs, material=material))
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mesh.vertex_normals
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if verbose:
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print(f"✅ RAW GLB: Generated {len(mesh.vertex_normals)} vertex normals")
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return mesh
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def to_glb(
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app_rep: Union[Strivec, Gaussian],
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mesh: MeshExtractResult,
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trellis/utils/render_utils.py
CHANGED
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@@ -75,7 +75,7 @@ def render_frames(sample, extrinsics, intrinsics, options={}, colors_overwrite=N
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if 'depth' not in rets: rets['depth'] = []
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# Apply gamma correction to video frames (Linear → sRGB)
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color_linear = res['color'].detach().cpu().numpy().transpose(1, 2, 0)
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-
color_srgb = np.power(np.clip(color_linear, 0, 1), 1.0/2.
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rets['color'].append(np.clip(color_srgb * 255, 0, 255).astype(np.uint8))
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if 'percent_depth' in res:
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rets['depth'].append(res['percent_depth'].detach().cpu().numpy())
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if 'depth' not in rets: rets['depth'] = []
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# Apply gamma correction to video frames (Linear → sRGB)
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color_linear = res['color'].detach().cpu().numpy().transpose(1, 2, 0)
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+
color_srgb = np.power(np.clip(color_linear, 0, 1), 1.0/2.2) # Standard gamma 2.2
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rets['color'].append(np.clip(color_srgb * 255, 0, 255).astype(np.uint8))
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if 'percent_depth' in res:
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rets['depth'].append(res['percent_depth'].detach().cpu().numpy())
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